Executive SummaryA model is developed to predict traffic levels in transport networks used to backhaul LTE eNodeBs.Backhaul traffic is made up of a number of different components of which user plane data is the largest,comprising around 80-90% of overall traffic, slightly less when IPsec encryption is added. The remainderconsists of the transport protocol overhead and traffic forwarding to another base-station during handover.Network signalling, management and synchronisation were assumed to be negligible.User plane traffic was depends on the characteristics of cell throughput that can be delivered by the LTE airinterface. Simulations of LTE cell throughput showed very high peaks were possible, corresponding to themaximum UE (user equipment) capabilities of up to 150Mbps. However, such peaks were only found tooccur under very light network loads of less than one user per cell. During ‘busy times’ with high user trafficdemands, cell throughputs were significantly lower than the quiet time peaks: A heavily loaded 20MHz 2x2LTE downlink cell limits at around 20Mbps cell throughput. In this scenario, the overall spectral efficiency ofthe cell is brought down by the presence of ‘cell edge users’, with poor signal quality and correspondingly lowdata rates.These results reveal that the cell throughput characteristics for data carrying networks are quite different tothose of voice carrying networks. In a data dominated LTE network, the peak cell throughputs in thehundreds of Mbps will occur during quiet times. Conversely in voice dominated networks, cell throughput isrelated to the number of active calls, hence peaks occur during the ‘busy hours’. Since cell throughput peaksoccur rarely and during quiet times, it is assumed that they do not occur simultaneously on neighbouringcells. On the other hand, the ‘busy time’ mean traffic will occur on all cells at the same time. The total userplane traffic for a tri-cell eNodeB (an LTE base station) is modelled as the larger of the peak from one cell, orthe combined busy time mean of the three cells. The same rule is applied to the calculation of traffic frommultiple aggregated eNodeBs.For the LTE downlink, peak cell throughput is around 4-6x the busy time mean, so for backhaul trafficaggregates of less than 4-6 cells typical of the ‘last mile’ of the transport network, it is the quiet time peakthat dominates capacity provisioning. For aggregates of 6 or more cells (e.g. two or more tricell eNodeBs), itis the busy time mean that dominates provisioning of the ‘core’ and ‘aggregation’ regions of the transportnetwork. From a technical perspective, it may not seem practical to provision the last mile backhaul for apeak rate that rarely occurs in practice. However, the ability to deliver such rates may be driven by marketingrequirements, as consumers are more likely to select networks or devices which can advertise highermaximum rates.The results presented in this paper represent mature LTE networks with sufficient device penetration to fullyload all cells during the busy times. It is recognised that it may take several years to reach such a state, andeven then, not all cells may reach full load. The lighter levels of loading likely in the early years of thenetwork will reduce the ‘busy time mean’ figures applicable to the aggregation and core regions of thetransport network. However, the quiet time peaks if anything will be more prevalent, and so provisioning inthe last mile will have to accommodate them from day one.The transport provisioning figures given this paper are provided as guidelines to help the industry understandthe sorts of traffic levels and characteristics that LTE will demand. They should not be interpreted asrequirements, and it should be recognised that provisioning may need to be adjusted according to theparticular deployment conditions of individual RAN sites. Results are given for a range of uplink and downlinkscenarios applicable to Release 8 of the LTE specifications. These include 10MHz and 20MHz systembandwidths, various MIMO configurations, and different UE categories

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